Storms, Dryness Speed Up Amazon Biomass Turnover

Chinese Academy of Sciences Headquarters

Tropical forests store more than 60% of the world's vegetation biomass and are among the most important ecosystems for regulating the global carbon cycle and climate. However, their regulatory role is greatly influenced by the forests' carbon residence time—how long carbon remains in the vegetation biomass pool before it is released again into the atmosphere. This figure is tied to the rate of biomass turnover—how quickly vegetation is replaced through growth and mortality.

In a recent study of Amazonian forests, researchers from the South China Botanical Garden (SCBG) of the Chinese Academy of Sciences, in collaboration with Cornell University and several international research institutions, found that the residence time of carbon in Amazonian vegetation will continue to shorten as atmospheric drying intensifies and convective storm activity increases, thereby undermining the forests' long-term carbon storage capacity.

The results were published in Nature Climate Change on May 13.

Previous studies on the capacity of tropical forest carbon sinks mostly focused on vegetation productivity, while tree mortality and biomass carbon turnover have received far less attention. In addition, earlier studies largely relied on site-level observations.

"Given the high complexity and spatial heterogeneity of tropical forest ecosystems, limited field plots cannot fully capture large-scale spatial patterns and environmental drivers of biomass carbon turnover," said Dr. WU Donghai from SCBG, a corresponding author of the paper.

To address the challenge, the researchers—selecting Amazonian forests as their study focus—integrated satellite remote sensing with long-term forest plot observations to generate tree mortality estimates. They subsequently mapped the spatial patterns of tree mortality across Amazonian forests.

Building on a non-equilibrium carbon cycle framework, the study produced a spatially explicit map of biomass carbon turnover time across the region. The researchers then applied interpretable machine learning models to systematically evaluate the influence of environmental factors on biomass carbon turnover time.

They found that biomass carbon turnover time in Amazonian forests exhibits marked spatial heterogeneity and responds to environmental factors in strongly nonlinear ways.

Importantly, the researchers identified convective storms—extreme weather events often accompanied by short-duration heavy rainfall and strong winds—as a key climatic regulator of biomass carbon turnover time in Amazonian forests. Such storms were found to exert a stronger influence than drought stress-related indicators.

The study also projected that by the end of this century, biomass carbon turnover time in Amazonian forests will decline by about 3% on average under a low-emissions scenario, and by as much as 15% under a high-emissions scenario.

The findings not only deepen our understanding of the mechanisms underlying tropical forest carbon sink stability, but also provide key scientific support for improving the representation of biomass carbon turnover processes in Earth System Models, WU said.

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